Hong Zhao, Yijian Zeng, J. Wen, Xin Wang, Zuoliang Wang, X. Meng, Z. Su
Department of Water Resources, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, Netherlands College of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225, China The Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China The Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Water and Environment, Chang’an University, Xi’an 710054, China
{"title":"An Air-to-Soil Transition Model for Discrete Scattering-Emission Modelling at L-Band","authors":"Hong Zhao, Yijian Zeng, J. Wen, Xin Wang, Zuoliang Wang, X. Meng, Z. Su","doi":"10.34133/2021/3962350","DOIUrl":"https://doi.org/10.34133/2021/3962350","url":null,"abstract":"Department of Water Resources, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, Netherlands College of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225, China The Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China The Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Water and Environment, Chang’an University, Xi’an 710054, China","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":" ","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43443500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Crop phenology is critical for agricultural management, crop yield estimation, and agroecosystem assessment. Traditionally, crop growth stages are observed from the ground, which is time-consuming and lacks spatial variability. Remote sensing Vegetation Index (VI) time series has been used to map land surface phenology (LSP) and relate to crop growth stages mostly after the growing season. In recent years, high temporal and spatial resolution remote sensing data have allowed near-real-time mapping of crop phenology within the growing season. This paper summarizes two classes of near-real-time mapping methods, i.e., curve-based and trend-based approaches. The curve-based approaches combine the time series VIs and crop growth stages from historical years with the current observations to estimate crop growth stages. The curve-based approaches are capable of a shortterm prediction. The trend-based approaches detect upward or downward trends from time series and confirm the trends using the increasing or decreasing momentum and VI thresholds. The trend-based approaches only use current observations. Both curve-based and trend-based approaches are promising in mapping crop growth stages timely. Nevertheless, mapping crop phenology near real-time is challenging since remote sensing observations are not always sensitive to crop growth stages. The accuracy of crop phenology detection depends on the frequency and availability of cloud-free observations within the growing season. Recent satellite datasets such as the harmonized Landsat and Sentinel-2 (HLS) are promising for mapping crop phenology within the season over large areas. Operational applications in the near future are feasible.
{"title":"Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities","authors":"F. Gao, Xiaoyang Zhang","doi":"10.34133/2021/8379391","DOIUrl":"https://doi.org/10.34133/2021/8379391","url":null,"abstract":"Crop phenology is critical for agricultural management, crop yield estimation, and agroecosystem assessment. Traditionally, crop growth stages are observed from the ground, which is time-consuming and lacks spatial variability. Remote sensing Vegetation Index (VI) time series has been used to map land surface phenology (LSP) and relate to crop growth stages mostly after the growing season. In recent years, high temporal and spatial resolution remote sensing data have allowed near-real-time mapping of crop phenology within the growing season. This paper summarizes two classes of near-real-time mapping methods, i.e., curve-based and trend-based approaches. The curve-based approaches combine the time series VIs and crop growth stages from historical years with the current observations to estimate crop growth stages. The curve-based approaches are capable of a shortterm prediction. The trend-based approaches detect upward or downward trends from time series and confirm the trends using the increasing or decreasing momentum and VI thresholds. The trend-based approaches only use current observations. Both curve-based and trend-based approaches are promising in mapping crop growth stages timely. Nevertheless, mapping crop phenology near real-time is challenging since remote sensing observations are not always sensitive to crop growth stages. The accuracy of crop phenology detection depends on the frequency and availability of cloud-free observations within the growing season. Recent satellite datasets such as the harmonized Landsat and Sentinel-2 (HLS) are promising for mapping crop phenology within the season over large areas. Operational applications in the near future are feasible.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"2021 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2021-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46266445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kai Yan, Dongxiao Zou, G. Yan, H. Fang, M. Weiss, M. Rautiainen, Y. Knyazikhin, R. Myneni
The MODIS LAI/FPAR products have been widely used in various fields since their first public release in 2000. This review intends to summarize the history, development trends, scientific collaborations, disciplines involved, and research hotspots of these products. Its aim is to intrigue researchers and stimulate new research direction. Based on literature data from the Web of Science (WOS) and associated funding information, we conducted a bibliometric visualization review of the MODIS LAI/FPAR products from 1995 to 2020 using bibliometric and social network analysis (SNA) methods. We drew the following conclusions: (1) research based on the MODIS LAI/FPAR shows an upward trend with a multiyear average growth rate of 24.9% in the number of publications. (2) Researchers from China and the USA are the backbone of this research area, among which the Chinese Academy of Sciences (CAS) is the core research institution. (3) Research based on the MODIS LAI/FPAR covers a wide range of disciplines but mainly focus on environmental science and ecology. (4) Ecology, crop production estimation, algorithm improvement, and validation are the hotspots of these studies. (5) Broadening the research field, improving the algorithms, and overcoming existing difficulties in heterogeneous surface, scale effects, and complex terrains will be the trend of future research. Our work provides a clear view of the development of the MODIS LAI/FPAR products and valuable information for scholars to broaden their research fields.
MODIS LAI/FPAR产品自2000年首次公开发布以来，已广泛应用于各个领域。本综述旨在总结这些产品的历史、发展趋势、科学合作、涉及的学科和研究热点。其目的是吸引研究人员并激发新的研究方向。基于科学网（WOS）的文献数据和相关资助信息，我们使用文献计量和社会网络分析（SNA）方法对1995年至2020年的MODIS LAI/FPAR产品进行了文献计量可视化综述。我们得出以下结论：（1）基于MODIS LAI/FPAR的研究显示出上升趋势，出版物数量多年平均增长率为24.9%。（2） 中国和美国的研究人员是这一研究领域的中坚力量，其中中国科学院（CAS）是核心研究机构。（3） 基于MODIS LAI/FPAR的研究涵盖了广泛的学科，但主要集中在环境科学和生态学方面。（4） 生态学、作物产量估计、算法改进和验证是这些研究的热点。（5） 拓宽研究领域，改进算法，克服异质表面、尺度效应和复杂地形中存在的困难将是未来研究的趋势。我们的工作为MODIS LAI/FPAR产品的发展提供了清晰的视角，并为学者拓宽研究领域提供了宝贵的信息。
{"title":"A Bibliometric Visualization Review of the MODIS LAI/FPAR Products from 1995 to 2020","authors":"Kai Yan, Dongxiao Zou, G. Yan, H. Fang, M. Weiss, M. Rautiainen, Y. Knyazikhin, R. Myneni","doi":"10.34133/2021/7410921","DOIUrl":"https://doi.org/10.34133/2021/7410921","url":null,"abstract":"The MODIS LAI/FPAR products have been widely used in various fields since their first public release in 2000. This review intends to summarize the history, development trends, scientific collaborations, disciplines involved, and research hotspots of these products. Its aim is to intrigue researchers and stimulate new research direction. Based on literature data from the Web of Science (WOS) and associated funding information, we conducted a bibliometric visualization review of the MODIS LAI/FPAR products from 1995 to 2020 using bibliometric and social network analysis (SNA) methods. We drew the following conclusions: (1) research based on the MODIS LAI/FPAR shows an upward trend with a multiyear average growth rate of 24.9% in the number of publications. (2) Researchers from China and the USA are the backbone of this research area, among which the Chinese Academy of Sciences (CAS) is the core research institution. (3) Research based on the MODIS LAI/FPAR covers a wide range of disciplines but mainly focus on environmental science and ecology. (4) Ecology, crop production estimation, algorithm improvement, and validation are the hotspots of these studies. (5) Broadening the research field, improving the algorithms, and overcoming existing difficulties in heterogeneous surface, scale effects, and complex terrains will be the trend of future research. Our work provides a clear view of the development of the MODIS LAI/FPAR products and valuable information for scholars to broaden their research fields.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"2021 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42050813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chuanmin Hu, Yingcheng Lu, Shaojie Sun, Yongxue Liu
Optical remote sensing (ORS) of reflected sun light has been used to assess oil spills in the ocean for several decades. While most applications are toward simple presence/absence detections based on the spatial contrast between oiled water and oil-free water, recent advances indicate the possibility of classifying oil types and quantifying oil volumes based on their spectral contrasts with oil-free water. However, a review of the current literature suggests that there is still confusion on whether this is possible and, if so, how. Here, based on the recent findings from numerical models, laboratory measurements, and applications to satellite or airborne imagery, we attempt to clarify this situation by summarizing (1) the optics behind oil spill remote sensing, and in turn, (2) how to interpret optical remote sensing imagery based on optical principles. In the end, we discuss the existing limitations and challenges as well as pathways forward to advance ORS of oil spills.
{"title":"Optical Remote Sensing of Oil Spills in the Ocean: What Is Really Possible?","authors":"Chuanmin Hu, Yingcheng Lu, Shaojie Sun, Yongxue Liu","doi":"10.34133/2021/9141902","DOIUrl":"https://doi.org/10.34133/2021/9141902","url":null,"abstract":"Optical remote sensing (ORS) of reflected sun light has been used to assess oil spills in the ocean for several decades. While most applications are toward simple presence/absence detections based on the spatial contrast between oiled water and oil-free water, recent advances indicate the possibility of classifying oil types and quantifying oil volumes based on their spectral contrasts with oil-free water. However, a review of the current literature suggests that there is still confusion on whether this is possible and, if so, how. Here, based on the recent findings from numerical models, laboratory measurements, and applications to satellite or airborne imagery, we attempt to clarify this situation by summarizing (1) the optics behind oil spill remote sensing, and in turn, (2) how to interpret optical remote sensing imagery based on optical principles. In the end, we discuss the existing limitations and challenges as well as pathways forward to advance ORS of oil spills.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"2021 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2021-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48478057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-09DOI: 10.36023/UJRS.2021.8.1.188
O. Ulytsky, K. Boiko
The article highlights the aspects of RSE technologies adaptation during the forward hydrogeological predictions development and for the purposes of the surface flooding zones spreading estimation within coal-mines fields, being flooded. Previously developed numerical geofiltration model allows to return filtration settings of the massif of rocks, that was broken due to coal extraction, and to identify the influence features of the mine workings flooding regime on the general hydrodynamic settings around the flooded mines. As a result of geofiltration modeling the forecast cartographic scheme of groundwater table level position at the final stage of mine workings flooding was obtained. To take into account the influence of surface subsidence over the mine workings on flooding zones distribution, the values of maximum possible vertical surface displacements over the mine workings contours were calculated, based on geological and surveying data. The relief mathematical model was developed with given expected vertical deformations using the GIS-techniques and the original DEM of the territory.The result of the radar satellites images processing is a cartographic model that demonstrates the intensity of uplift movements of the earth surface. Areas of distribution of large-amplitude movements (10-20 mm/year) were determines. As a result, an updated scheme of the forecasted flooded zones was developed.
{"title":"RSE-based flooding prediction within territories of closed coal mines of Ukraine","authors":"O. Ulytsky, K. Boiko","doi":"10.36023/UJRS.2021.8.1.188","DOIUrl":"https://doi.org/10.36023/UJRS.2021.8.1.188","url":null,"abstract":"The article highlights the aspects of RSE technologies adaptation during the forward hydrogeological predictions development and for the purposes of the surface flooding zones spreading estimation within coal-mines fields, being flooded. Previously developed numerical geofiltration model allows to return filtration settings of the massif of rocks, that was broken due to coal extraction, and to identify the influence features of the mine workings flooding regime on the general hydrodynamic settings around the flooded mines. As a result of geofiltration modeling the forecast cartographic scheme of groundwater table level position at the final stage of mine workings flooding was obtained. To take into account the influence of surface subsidence over the mine workings on flooding zones distribution, the values of maximum possible vertical surface displacements over the mine workings contours were calculated, based on geological and surveying data. The relief mathematical model was developed with given expected vertical deformations using the GIS-techniques and the original DEM of the territory.The result of the radar satellites images processing is a cartographic model that demonstrates the intensity of uplift movements of the earth surface. Areas of distribution of large-amplitude movements (10-20 mm/year) were determines. As a result, an updated scheme of the forecasted flooded zones was developed.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"8 1","pages":"18-25"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45212987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-09DOI: 10.36023/UJRS.2021.8.1.189
V. Pokalyuk, I. Lomakin, V. Verkhovtsev, V. Kochelab
Modern high-precision global digital 3-d models of the relief of the continents and the ocean floor (SRTM, GEBCO) are the objective basis to clarify the structure and features of the organization of the planetary fault network of of the Black Sea region and adjacent areas of the Mediterranean mobile belt and surrounding platform areas, to find out the location of the main transregional supermegalineaments forming the deep structural-tectonic framework of the territory. A complete consistency of the structural plan of faults and fault zones within the sea areas and continental surroundings is established. The structural position of the Black Sea basin as a whole is determined by its location at the intersection area (superposition, interference) of the diagonal (subdiagonal) transcontinental tectonolinament belts: the north-west – Elba-Zagros, Caucasus-Kopetdag, and the north-east – Atlas- Black Sea. The absence of large-scale lateral displacements at the intersection nodes of differently oriented supermegalineament systems indicates the relative autonomous stationarity and inheritance of the formation of the lyneament framework during the entire Mezozoic-Cenozoic and relatively low-shear nature of its implementation. This feature of the Black Sea region structural pattern significantly limits the possibility of using neomobilistic geodynamic models to explain the history of the geological development of the region. The strict consistency and orderliness of the lineament framework can be ensured only by global planetary factors associated with the influence of the rotational regime of the Earth's shells on the stress distribution in the lithosphere.
{"title":"Tectonolinament framework of the Black Sea region and the surrounding areas","authors":"V. Pokalyuk, I. Lomakin, V. Verkhovtsev, V. Kochelab","doi":"10.36023/UJRS.2021.8.1.189","DOIUrl":"https://doi.org/10.36023/UJRS.2021.8.1.189","url":null,"abstract":"Modern high-precision global digital 3-d models of the relief of the continents and the ocean floor (SRTM, GEBCO) are the objective basis to clarify the structure and features of the organization of the planetary fault network of of the Black Sea region and adjacent areas of the Mediterranean mobile belt and surrounding platform areas, to find out the location of the main transregional supermegalineaments forming the deep structural-tectonic framework of the territory. A complete consistency of the structural plan of faults and fault zones within the sea areas and continental surroundings is established. The structural position of the Black Sea basin as a whole is determined by its location at the intersection area (superposition, interference) of the diagonal (subdiagonal) transcontinental tectonolinament belts: the north-west – Elba-Zagros, Caucasus-Kopetdag, and the north-east – Atlas- Black Sea. The absence of large-scale lateral displacements at the intersection nodes of differently oriented supermegalineament systems indicates the relative autonomous stationarity and inheritance of the formation of the lyneament framework during the entire Mezozoic-Cenozoic and relatively low-shear nature of its implementation. This feature of the Black Sea region structural pattern significantly limits the possibility of using neomobilistic geodynamic models to explain the history of the geological development of the region. The strict consistency and orderliness of the lineament framework can be ensured only by global planetary factors associated with the influence of the rotational regime of the Earth's shells on the stress distribution in the lithosphere.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"8 1","pages":"26-44"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47635173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-09DOI: 10.36023/UJRS.2021.8.1.187
V. Yakimchuk, K. Sukhanov, O. Tomchenko
The methods for detecting environmental changes using two multispectral multispectral space images of the Earth, which can be used to assess changes in the ecological and geological environment to control the dynamics of processes in real time, in order to prevent environmental emergencies. The creation and operation of a system of continuous geoecological monitoring based on space information involves the detection of relative changes in the environment on two multispectral space images of the Earth, obtained after a certain period of time. To do this, it is necessary to develop and apply adaptive methods (indices) for detecting relative changes. Three methods are proposed that are adapted to specific images to find the optimal solution that maximizes the relative changes in two different time multispectral space images of the Earth. The first method selects one optimal channel from all channels of the space image, the second method - two optimal channels from all channels and the third - four optimal channels from all channels. There are known methods that assess the presence or absence of changes in two space images at different times, but they do not provide information about the direction of changes. The proposed indices can take positive and negative values, reflecting the trend of changes on the ground. The negative values of the indices obtained in the area near the village of Solotvyno, Tyachiv district, Zakarpattia region, correspond to the areas with the most dynamic changes in the environment of such exogenous processes as karst funnels and lakes, and positive values correspond to increasing vegetation areas. The results of comparing the application of the change detection index on two different multispectral space images of the Earth on four, two channels and one channel showed that increasing the number of channels can give a more reasonable picture of changes, but to concretize these changes requires ground-based observations.
{"title":"Adaptive methods of detecting environmental changes using multispectral satellite images on the Earth for example territory Solotvyno","authors":"V. Yakimchuk, K. Sukhanov, O. Tomchenko","doi":"10.36023/UJRS.2021.8.1.187","DOIUrl":"https://doi.org/10.36023/UJRS.2021.8.1.187","url":null,"abstract":"The methods for detecting environmental changes using two multispectral multispectral space images of the Earth, which can be used to assess changes in the ecological and geological environment to control the dynamics of processes in real time, in order to prevent environmental emergencies. The creation and operation of a system of continuous geoecological monitoring based on space information involves the detection of relative changes in the environment on two multispectral space images of the Earth, obtained after a certain period of time. To do this, it is necessary to develop and apply adaptive methods (indices) for detecting relative changes. Three methods are proposed that are adapted to specific images to find the optimal solution that maximizes the relative changes in two different time multispectral space images of the Earth. The first method selects one optimal channel from all channels of the space image, the second method - two optimal channels from all channels and the third - four optimal channels from all channels. There are known methods that assess the presence or absence of changes in two space images at different times, but they do not provide information about the direction of changes. The proposed indices can take positive and negative values, reflecting the trend of changes on the ground. The negative values of the indices obtained in the area near the village of Solotvyno, Tyachiv district, Zakarpattia region, correspond to the areas with the most dynamic changes in the environment of such exogenous processes as karst funnels and lakes, and positive values correspond to increasing vegetation areas. The results of comparing the application of the change detection index on two different multispectral space images of the Earth on four, two channels and one channel showed that increasing the number of channels can give a more reasonable picture of changes, but to concretize these changes requires ground-based observations.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"8 1","pages":"10-17"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47496500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.7780/KJRS.2021.37.1.10
Cheonggil Jin, Chuluong Choi
In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.
{"title":"The Assessment of Cross Calibration/Validation Accuracy for KOMPSAT-3 Using Landsat 8 and 6S","authors":"Cheonggil Jin, Chuluong Choi","doi":"10.7780/KJRS.2021.37.1.10","DOIUrl":"https://doi.org/10.7780/KJRS.2021.37.1.10","url":null,"abstract":"In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"37 1","pages":"123-137"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71375727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.7780/KJRS.2021.37.1.5
M. Fadhillah, Chang-Wook Lee
An earthquake occurred on 17 November 2017 in Pohang, South Korea with a strength of 5.4 Mw. This is the second strongest earthquake recorded by local authorities since the equipment was first installed. In order to improve understanding of earthquakes and surface deformation, many studies have been conducted according to these phenomena. In this research, we will estimate the surface deformation using the Okada model equation. The SAR images of three satellites with different wavelengths (ALOS-2, Cosmo SkyMed and Sentinel-1) were used to produce the interferogram pairs. The interferogram is used as a reference for surface deformation changes by using Okada to determine the source of surface deformation that occurs during an earthquake. The Non-linear optimization (Levemberg-Marquadrt algorithm) and Monte Carlo restart was applied to optimize the fault parameter on modeling process. Based on the modeling results of each satellite data, the fault geometry is ~6 km length, ~2 km width and ~5 km depth. The root mean square error values in the surface deformation model results for Sentinel, CSK and ALOS are 0.37 cm, 0.79 cm and 1.47 cm, respectively. Furthermore, the results of this modeling can be used as learning material in understanding about seismic activity to minimize the impacts that arise in the future.
{"title":"The Estimated Source of 2017 Pohang Earthquake Using Surface Deformation Modeling Based on Multi-Frequency InSAR Data","authors":"M. Fadhillah, Chang-Wook Lee","doi":"10.7780/KJRS.2021.37.1.5","DOIUrl":"https://doi.org/10.7780/KJRS.2021.37.1.5","url":null,"abstract":"An earthquake occurred on 17 November 2017 in Pohang, South Korea with a strength of 5.4 Mw. This is the second strongest earthquake recorded by local authorities since the equipment was first installed. In order to improve understanding of earthquakes and surface deformation, many studies have been conducted according to these phenomena. In this research, we will estimate the surface deformation using the Okada model equation. The SAR images of three satellites with different wavelengths (ALOS-2, Cosmo SkyMed and Sentinel-1) were used to produce the interferogram pairs. The interferogram is used as a reference for surface deformation changes by using Okada to determine the source of surface deformation that occurs during an earthquake. The Non-linear optimization (Levemberg-Marquadrt algorithm) and Monte Carlo restart was applied to optimize the fault parameter on modeling process. Based on the modeling results of each satellite data, the fault geometry is ~6 km length, ~2 km width and ~5 km depth. The root mean square error values in the surface deformation model results for Sentinel, CSK and ALOS are 0.37 cm, 0.79 cm and 1.47 cm, respectively. Furthermore, the results of this modeling can be used as learning material in understanding about seismic activity to minimize the impacts that arise in the future.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"37 1","pages":"57-67"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48606512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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